Biomedical subjects

John J Rogus

Publications and source records attributed to John J Rogus.

7 recordsLinked to original sources

PubMed2006

Genetics of Kidneys in Diabetes (GoKinD) study: a genetics collection available for identifying genetic susceptibility factors for diabetic nephropathy in type 1 diabetes.

The Genetics of Kidneys in Diabetes (GoKinD) study is an initiative that aims to identify genes that are involved in diabetic nephropathy. A large number of individuals with type 1 diabetes were screened to identify two subsets, one with clear-cut kidney disease and another with normal renal status despite long-term diabetes. Those who met additional entry criteria and consented to participate were enrolled. When possible, both parents also were enrolled to form family trios. As of November 2005, GoKinD included 3075 participants who comprise 671 case singletons, 623 control singletons, 272 case trios, and 323 control trios. Interested investigators may request the DNA collection and corresponding clinical data for GoKinD participants using the instructions and application form that are available at http://www.gokind.org/access. Participating scientists will have access to three data sets, each with distinct advantages. The set of 1294 singletons has adequate power to detect a wide range of genetic effects, even those of modest size. The set of case trios, which has adequate power to detect effects of moderate size, is not susceptible to false-positive results because of population substructure. The set of control trios is critical for excluding certain false-positive results that can occur in case trios and may be particularly useful for testing gene-environment interactions. Integration of the evidence from these three components into a single, unified analysis presents a challenge. This overview of the GoKinD study examines in detail the power of each study component and discusses analytic challenges that investigators will face in using this resource.

Adult↗

PubMed2006

A genome-wide linkage scan for genes controlling variation in renal function estimated by serum cystatin C levels in extended families with type 2 diabetes.

We performed a variance components linkage analysis of renal function, measured as glomerular filtration rate (GFR), in 63 extended families with multiple members with type 2 diabetes. GFR was estimated from serum concentrations of cystatin C and creatinine in 406 diabetic and 428 nondiabetic relatives. Results for cystatin C were summarized because they are superior to creatinine results. GFR aggregates in families with significant heritability (h(2)) in diabetic (h(2) = 0.45, P < 1 x 10(-5)) and nondiabetic (h(2) = 0.36, P < 1 x 10(-3)) relatives. Genetic correlation (r(G) = 0.35) between the GFR of diabetic and nondiabetic relatives was less than one (P = 0.01), suggesting that genes controlling GFR variation in these groups are different. Linkage results supported this interpretation. In diabetic relatives, linkage was strong on chromosome 2q (logarithm of odds [LOD] = 4.1) and suggestive on 10q (LOD = 3.1) and 18p (LOD = 2.2). In nondiabetic relatives, linkage was suggestive on 3q (LOD = 2.2) and 11p (LOD = 2.1). When diabetic and nondiabetic relatives were combined, strong evidence for linkage was found only on 7p (LOD = 4.0). In conclusion, partially distinct sets of genes control GFR variation in relatives with and without diabetes on chromosome 2q, possibly on 10q and 18p in the former, and on 7p in both. None of these genes overlaps with genes controlling variation in urinary albumin excretion.

Adult↗

PubMed2005

A novel framework for sib pair linkage analysis.

Sib pair linkage analysis of a dichotomous trait is a popular method for narrowing the search for genes that influence complex diseases. Although the pedigree structures are uncomplicated and the underlying genetic principles straightforward, a surprising degree of complexity is involved in implementing a sib pair study and interpreting the results. Ascertainment may be based on affected, discordant, or unaffected sib pairs, as well as on pairs defined by threshold values for quantitative traits, such as extreme discordant sib pairs. To optimize power, various domain restrictions and null hypotheses have been proposed for each of these designs, yielding a wide array of choices for the analyst. To begin, we systematically classify the major sources of discretion in sib pair linkage analysis. Then, we extend the work of Kruglyak and Lander (1995), to bring the various forms into a unified framework and to facilitate a more general approach to the analysis. Finally, we describe a new, freely available computer program, Splat (Sib Pair Linkage Analysis Testing), that can perform any sib pair statistical test currently in use, as well as any user-defined test yet to be proposed. Splat uses the expectation maximization algorithm to calculate maximum-likelihood estimates of sharing (subject to user-specified conditions) and then plots LOD scores versus chromosomal position. It includes a novel grid-scanning capability that enables simultaneous visualization of multiple test statistics. This can lead to further insight into the genetic basis of the disease process under consideration. In addition, phenotype definitions can be modified without the recalculation of inheritance vectors, thereby providing considerable flexibility for exploratory analysis. The application of Splat will be illustrated with data from studies on the genetics of diabetic nephropathy.

Algorithms↗

PubMed2003

Identification of a common risk haplotype for diabetic nephropathy at the protein kinase C-beta1 (PRKCB1) gene locus.

Abnormal activation of protein kinase C-beta isoforms in the diabetic state has been implicated in the development of diabetic nephropathy. It is thus plausible that DNA sequence differences in the protein kinase C-beta1 gene (PRKCB1), which encodes both betaI and betaII isoforms, may influence susceptibility to nephropathy. Nine single-nucleotide polymorphisms (SNP) in PRKCB1 were tested for association with diabetic nephropathy in type I diabetes mellitus, by using both case-control and family-study designs. Allele and genotype distributions of two SNP in the promoter (--1504C/T and --546C/G) differed significantly between case patients and control patients (P < 0.05). These associations were particularly strong with diabetes mellitus duration of <24 yr (P = 0.002). The risk of diabetic nephropathy was higher among carriers of the T allele of the --1504C/T SNP, compared with noncarriers (odds ratio, 2.54; 95% confidence interval, 1.39 to 4.62), and among carriers of the G allele of the --546C/G SNP (odds ratio, 2.45; 95% confidence interval, 1.37 to 4.38). Among individuals with diabetes mellitus duration of >/==" BORDER="0">24 yr, these two SNP were not associated with diabetic nephropathy. These positive findings were confirmed by using the family-based transmission disequilibrium test. The T-G haplotype, with both risk alleles, was transmitted more frequently than expected from heterozygous parents to offspring who developed diabetic nephropathy during the first 24 yr of diabetes mellitus. It is concluded that DNA sequence differences in the promoter of PRKCB1 contribute to diabetic nephropathy susceptibility in type I diabetes mellitus.

Adult↗

PubMed2002

A method for developing high-density SNP maps and its application at the type 1 angiotensin II receptor (AGTR1) locus.

Evaluating the potential genetic components of complex disease will likely be aided through the use of dense polymorphism maps. Previously, we reported evidence for linkage with diabetic nephropathy on chromosome 3q in a region encompassing the type 1 angiotensin II receptor (AGTR1) gene. To further investigate any role for this gene in disease onset, we set out to design a dense polymorphism map spanning the AGTR1 locus for the purpose of association studies. Toward this goal, we have developed a technique for rapid identification of polymorphisms in long stretches of genomic DNA. This approach uses long-range PCR, DNA pooling, and transposon-based DNA sequencing. Using this technique, we efficiently validated and genotyped 18 polymorphisms spanning the 60.5-kb AGTR1 locus. Our panel of polymorphisms has an average spacing of 3.2 kb and an average minor allele frequency of 24%.

Base Sequence↗

PubMed2002

Polymorphism in ecto-nucleotide pyrophosphatase/phosphodiesterase 1 gene (ENPP1/PC-1) and early development of advanced diabetic nephropathy in type 1 diabetes.

A polymorphism in the ecto-nucleotide pyrophosphatase/phosphodiesterase 1 gene (ENPP1) (previously known as PC-1), resulting in an amino acid change from lysine to glutamine at codon 121 (K121Q), is associated with insulin resistance. A small follow-up study of patients with type 1 diabetes and proteinuria found that renal function declines more rapidly in carriers of the Q variant than in noncarriers. To examine this finding further, we conducted a large case-control study and a family-based study. Genomic DNA was obtained from 659 patients: 307 with normal urinary albumin excretion despite diabetes duration of >15 years (control subjects) and 352 with advanced diabetic nephropathy, of whom 200 had persistent proteinuria and 152 had end-stage renal disease (ESRD). Individuals were genotyped for Q and K variants using a previously described protocol. The frequency of Q variant carriers was 21.5% in control subjects, 31.5% in subjects with proteinuria, and 32.2% in subjects with ESRD (P = 0.012). In a stratified analysis according to duration of diabetes, the risk of early-onset ESRD for carriers of the Q variant was 2.3 times that for noncarriers (95% CI, 1.2-4.6). The Q variant was not associated with late-onset ESRD. Similar findings were obtained in a family-based study. We conclude that carriers of the Q variant of ENPP1 are at increased risk for developing ESRD early in the course of type 1 diabetes.

Adult↗

PubMed2002

Genetic studies of late diabetic complications: the overlooked importance of diabetes duration before complication onset.

Genes play a role in many processes underlying late diabetic complications, but efforts to identify genetic variants have produced disappointing and contradictory results. Here, we evaluate whether the study designs and analytic methods commonly being used are optimal for finding susceptibility genes for diabetic complications. We do so by generating plausible genetic models and assessing the performance of case-control and family-based trio study designs. What emerges as a key determinant of success is duration of diabetes. This perspective focuses on duration of diabetes before complication onset and its influence on the ability to detect major and minor gene effects. It does not delve into the distinct effect of duration after complication onset, which can enrich case subjects with genotypes conferring survival advantage. We use clinically diagnosed nephropathy in type 1 diabetes to show how ignoring duration can result in considerable power loss in both case-control and family-based trio designs. We further show how, under certain circumstances, disregard for duration information can paradoxically lead to implicating nonrisk alleles as causative. Our results indicate that problems can be minimized by selecting case subjects with short diabetes duration and, to a lesser extent, control subjects with long duration or, perhaps, by adjusting for duration during analysis.

Case-Control Studies↗